Assessment of abdominal organ dose and image quality in varying arc trajectory interventional C-arm cone beam CT

Published:September 09, 2022DOI:


      • Organ dose and image quality vary on the exposure arc trajectory in C-arm CBCT.
      • Proposed coefficients may be used to estimate organ dose on the current CBCT unit.
      • Image quality is highest in volumes located close to the system’s isocenter.
      • Selection of task-specific protocol optimizes organ dose at an acceptable level of image quality.



      The aim of this study was to investigate the effect of varying arc exposure trajectory on radiation dose to radiosensitive organs and to assess image quality in abdominal C-arm cone beam computed tomography (CBCT) interventional procedures using a latest generation system.


      An anthropomorphic phantom that simulates the average adult individual was used. Individual-specific Monte Carlo (MC) simulation dosimetry was performed to estimate organ doses (OD) in abdominal C-arm CBCT. Seven examination protocols prescribed by the system for vascular and soft tissue CBCT, were simulated. These protocols are differentiated in the range of the arc exposure trajectory and the level of radiation dose delivered to the patient. OD was estimated for liver, adrenals, kidneys, pancreas, stomach, gall bladder, spleen, bone and skin. Image noise, signal to noise ratio (SNR), contrast to noise ratio (CNR) and in-plane spatial resolution were assessed using CT-specific image quality assessment phantoms.


      OD was found to depend on the range of arc trajectory and was higher for posterior located organs. In vascular protocols OD ranged from 4.75 mGy for skin to 0.60 mGy for bone. Image noise was higher in vascular protocols than in soft tissue ones. SNR and CNR were significantly modified among different soft tissue protocols (P < 0.05). In-plane spatial resolution was found 0.80 lp/mm in vascular as opposed to 0.41 lp/mm in soft tissue protocols.


      The current results may be used to estimate OD for different examination protocols and enable operators choose the appropriate acquisition protocol on the preprogrammed interventional task.


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        • Fahrig R.
        • Jaffray D.A.
        • Sechopoulos I.
        • Webster S.J.
        Flat-panel conebeam CT in the clinic: history and current state.
        J Med Imaging. 2021; 8: 0521151-05211540
        • Tsai Y.
        • Shih J.H.
        • Hwang H.
        • Chiu N.
        • Lee R.
        • Tseng H.
        • et al.
        Early prediction of 1-year tumor response of hepatocellular carcinoma with lipiodol deposition pattern through post-embolization cone-beam computed tomography during conventional transarterial chemoembolization.
        Eur Radiol. 2021; 31: 7464-7475
        • Gutierrez D.
        • Gurajala R.K.
        • Kapoor B.
        • Setser R.
        • Karuppasamy K.
        Relationship between cone-beam CT technique and diagnostic usefulness in patients undergoing embolotherapy for hepatocellular carcinoma.
        Clin Radiol. 2017; 72: 993e1-e6
        • Lucatelli P.
        • Corona M.
        • Argiro R.
        • Anzidei M.
        • Vallati G.
        • Fanelli F.
        • et al.
        Impact of 3D Rotational Angiography on Liver Embolization Procedures: Review of Technique and Applications.
        Cardiovasc Intervent Radiol. 2015; 38: 523-535
      1. ICRP International Commission on Radiological Protection, The 2007 recommendations of the International Commission on Radiological Protection ICRP Publication 103, 2007.

        • Bootsma G.J.
        • Verhaegen F.
        • Jaffray D.A.
        Efficient scatter distribution estimation and correction in CBCT using concurrent Monte Carlo fitting.
        Med Phys. 2015; 42: 54-68
        • Tang X.
        • Krupinski E.A.
        • Xie H.
        • Stillman A.E.
        On the data acquisition, image reconstruction, cone beam artifacts, and their suppression in axial MDCT and CBCT-A review.
        Med Phys. 2018; 45: 761-782
        • Siewerdsen J.H.
        • Uneri A.
        • Hernandez A.M.
        • Burket G.W.
        • Boone J.M.
        Cone-beam CT dose and imaging performance evaluation with a modular, multipurpose phantom.
        Med Phys. 2020; 47: 467-479
      2. Gardner SJ, Studenski MT, Giaddui T, Cui Y, Galvin J, Yu Y, et al. Investigation into image quality and dose for different patient geometries with multiple cone-beam CT systems. Med Phys. 2017;41:0319081-11.

        • Choi J.H.
        • Constantin D.
        • Ganguly A.
        • Girard E.
        • Morin R.
        • Dixon R.L.
        • et al.
        Practical dose point-based methods to characterize dose distribution in a stationary elliptical body phantom for a cone-beam C-arm CT system.
        Med Phys. 2015; 42: 4920-4932
        • Haba T.
        • Yasui K.
        • Saito Y.
        • Kobayashi M.
        • Koyama S.
        A new Cone-beam computed tomography dosimetry methods providing optimal measurement positions: A Monte Carlo Study.
        Physica Med. 2021; 81: 130-140
        • Kenny E.
        • Caldwell D.
        • Lewis M.
        Practical radiation dosimetry across a variety of CBCT devices in radiology.
        Physica Med. 2020; 71: 3-6
        • Deak P.
        • van Straten M.
        • Shrimpton P.C.
        • Zankl M.
        • Kalender W.A.
        Validation of a Monte Carlo tool for patient-specific dose simulations in multi-slice computed tomography.
        Eur Radiol. 2008; 18: 759-772
        • Papadakis A.E.
        • Perisinakis K.
        • Damilakis J.
        Development of a method to estimate organ doses for pediatric CT examinations.
        Med Phys. 2016; 43: 2108-2117
      3. Papadakis AE, Damilakis J, Organ doses and normalized organ doses for various age groups in ultralow dose pediatric C-arm cone-beam CT. Eur Radiol. 2022. doi: 10.1007/s00330-022-08767-7. Online ahead of print.

      4. IAEA. Human Health Reports No. 5 Subject Classification: 0103-Medical physics “Status of Computed Tomography Dosimetry for Wide Cone Beam Scanners” STI/PUB/1528 (ISBN: 978-92-0-120610-7). 2011.

      5. IEC International Electro Technical Commission. Medical electrical equipment–Part 2-44: Particular requirements for the basic safety and essential performance of x-ray equipment for computed tomography. IEC 60601-2-44 ed3.1. 2012.

        • Suzuki S.
        • Furui S.
        • Yamaguchi I.
        • Yamagishi M.
        • Watanabe A.
        • Abe T.
        • et al.
        Effective dose during abdominal three-dimensional imaging with a flat-panel detector angiography system.
        Radiology. 2009; 250: 545-550
      6. Kwok YM, Irani FG, Tay KH, Yang CC, Padre CG, Tan BS. Effective dose estimates for cone beam computed tomography in interventional radiology. Eur Radiol. 2013;23:3197-04.

      7. Dosimetry in diagnostic radiology: An international code of practice. International Atomic Energy Agency, Vienna 2007, Technical report series No. 457.